PROJECT SUMMARY Urinary tract infections (UTIs) are commonplace, drive extensive antibiotic use, and are becoming increasingly resistant to treatment. There is general agreement that the chemical composition of urine plays an influential role in UTI pathogenesis but this has been difficult to translate to clinical practice. Recently, we found wide individual differences in urine's ability to support antibacterial iron chelation by the innate immune protein siderocalin (SCN; also known as Lipocalin-2 or NGAL). Using mass spectrometry-based metabolomics, we linked these differences to a specific chemical class of human urinary metabolites. This and other work supports a functional role for urinary metabolites in innate antibacterial immunity. Clinical urinary pathogens posses numerous phenotypic and genetic adaptations to the urinary environment, suggesting multiple selective pressures related to urinary composition. Here we will identify human urinary metabolomic influences on UTI pathogenesis. Because human urine is a chemically complex biofluid, we will combine recent bioanalytical advances with contemporary data science approaches to identify metabolomic networks that influence bacterial growth and behavior. By identifying these networks, exploring their precise biochemical functions, and learning their physiologic origins we will provide a basis for translation to patient care. The proposed analyses and experiments represent a rigorous evaluation of our hypothesis that urinary composition plays an important role in infection resistance and should be targeted therapeutically to prevent or treat infections.